Can anyone help me on implementing gaussian noise on an ecg signal? If you want i can share my code. The problem is gaussian noise is 0 always.

sig = 1/abs(Fs) for i = 1:L gauss(i) = exp(-(i*i)/(2*sig*sig))/(sig*sqrt(pi*2)); dist(i) = gauss(i)+ x(i); i end

subplot(2,1,2); plot(t(1:L),dist(1:L)) title('Dist ECG Signal')

Answer 1

[Chunru]

Fs = 1; L = 128; 
x = zeros(L, 1);    % This can be your original signal
sig = 1/abs(Fs);    % std of Gaussian random noise 
%{
for i = 1:L 
    % This is Gassian pdf function, not Gaussian distributed time series
    gauss(i) = exp(-(i*i)/(2*sig*sig))/(sig*sqrt(pi*2)); 
    dist(i) = gauss(i)+ x(i); 
end
%}

y = x + randn(L,1) * sig;       % signal + Gaussian noise (doc randn)
plot((1:L), y) 
title('ECG Signal with Gaussian Noise added')

Answer 2

[LO]

I tried to fit some params,

you can use the function wgn (white gaussian noise, see documentation)

Fs = 20000;
sig = 1/abs(Fs) ;
L = 100;
x= rand(1,1000);
t=[1:1000];

for i = 1:L 
    gauss(i) = exp(-(i*i)/(2*sig*sig))/(sig*sqrt(pi*2)); 
    dist(i) = gauss(i)+ x(i); 
    i 

end


noise = wgn(1000,1,0);

subplot(2,1,1);

plot(t(1:L),noise(1:L)) 

title('white gaussian noise ECG Signal')

subplot(2,1,2); 

plot(t(1:L),dist(1:L)) 

title('Dist ECG Signal')